With recent developments in the wireless communication, use of wireless communication devices has become almost ubiquitous. These wireless devices include laptop computers, tablet computers, smart phones, as well as plethora of other wireless devices (car navigation devices, user-wearable navigation devices, and the like). Most, if not all, wireless devices are equipped with geo-position devices (for example, those using GPS technology for determining geo position of the wireless device, those using triangulation techniques, or the like).
Most of these wireless devices are further equipped with mapping and/or navigation applications (jointly referred herein below as a mapping application). A typical mapping application provides maps of various regions, for example, the user can use the mapping application to request a map of downtown of London, UK. The user can request such map by various means: by using the geo-location functionality of the wireless device (and a function known as “places near me” or a similar functionality of wireless devices), by typing in a postal code or a full address, etc.
The user can also use such mapping application to map routes between am origin position and a destination position. For example, where the wireless device is a smart phone, the user can use the mapping application to determine a driving route from a place in Brampton, Ontario, Canada to a place in Mississauga, Ontario, Canada by typing in a start address and a destination address. The mapping application will then create one or more routes (such as a fastest route, a route that avoids toll highways, a route that is associated with a shortest distance, etc.).
Some of these mapping applications are executed on wireless devices associated with user vehicles (such as portable GPS device or a GPS device built into modern passenger vehicles).
Some of these mapping applications (such as those provided by Yandex™ Maps, Yandex™ Navigator, Google™ Maps, Waze™, etc. provide an additional functionality of showing traffic information using the map interface of the mapping information.
With reference to FIG. 1, there is depicted a screenshot 100 of a mapping application, the screenshot 100 that can be shown on an example of the wireless electronic device, such as a smartphone, for example. The screenshot 100 shows a map 102, the map 102 depicting a map view of a particular geographical area having a plurality of route segments 104. The user of the electronic device may have requested route information about a route from a point A to a point B, marked on the map 102 accordingly in a dash-dotted line. There is a current position pointer 180 that depicts the current position associated with the wireless electronic device (which happens to be not on the requested route, as the user of the wireless electronic device may be planning a future route).
The map 102 further depicts traffic conditions information 106. In the depicted embodiment, the traffic conditions information 106 is overlaid over the plurality of route segments 104 to visually represent traffic conditions associated with the respective ones of the plurality of route segments 104. In the embodiments illustrated herein, the traffic conditions information 106 can be represented by a color (such as red for heavy traffic, blue for medium level traffic and green for no traffic), as well as (or instead of) a graphical representation (such as an arrow, which length depends on the associated traffic conditions).
The map further depicts a first type of auxiliary information indicator 108 and a second type of auxiliary information indicator 110. The first type of auxiliary information indicator 108 can be for example an indicator associated with accidents that occur along the plurality of route segments 104. The second type of auxiliary information indicator 110 can provide additional information about a particular point along the plurality of route segments 104. The additional information can be, for example, information about special driving conditions associated with the particular point along the plurality of route segments 104. For example, on multi-lane roads with flexible lanes (that can selectively accommodate traffic in one direction and another direction), the special driving conditions can outline when the given flexible lane is for the first direction and when the given flexible lane is for another direction.
The map 102 is further associated with the traffic congestion indicator 112. The traffic congestion indicator 112 can provide an indication of the overall traffic conditions associated with the map view (or a portion thereof) visible within the map 112. In the depicted example, the traffic congestion indicator 112 is implemented as a traffic light with a digit representing of the overall traffic conditions displayable therein—in this case, a digit between 0 and 10, 0 representing no traffic and 10 representing heavily congested traffic condition (commonly known as a “bumper to bumper” or a “parking lot” driving condition).
Generally speaking, the traffic information is representative of driving conditions along a pre-determined route. The traffic information can be representative of traffic conditions along the pre-determined route, taking into account traffic jams, accidents, road work, etc. The information about traffic jams for a segment of the pre-determined route is typically generated by calculating an average speed of drivers on that segment and comparing it to a reference speed. The average speed of drivers is typically calculated based on data collected from wireless devices associated with drivers, the wireless devices executing mapping applications.
Using an example of FIG. 2, there is depicted a portion of an actual road segment 202 (such as one that can be used to generate the map 102). The system collects movement data from wireless devices (that execute mapping applications) associated with vehicles moving along the actual road segment 202, such as a vehicle 206. The system collects information about the vehicle 206 entering and exiting a road segment 204 defined between a Point A and a Point B. The system collects such information from a plurality of vehicles that are similar to the vehicle 206, the plurality of vehicles moving through the same road segment.
Based on the travel patterns associated with the plurality of vehicles travelling through the road segment 204 (i.e. the time it takes to travel through the road segment, the length of the road segment, etc.), the system then calculates an average speed or an average time taken to travel through the road segment 204. Typically, the system calculates the average speed by recording a time stamp associated with the vehicle 206 entering the road segment 204, a time stamp associated with the vehicle 206 leaving the road segment 204; and knowing the distance of the road segment 204, the system calculates the average speed of the vehicle 206.
The system then compares such generated information to some pre-defined thresholds to determine traffic conditions. For example, using the road segment 204 as an example, average travel time of under one minute can be considered to be “no traffic” indicator, travel time of between one minute and two minutes can be considered to be “moderate traffic” indicator, and travel time of over three minutes can be indicative of a “heavy traffic” indicator.
US 2014/149028 discloses techniques for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).
US 2014/0163848 discloses a method of evaluating the driving behavior in a vehicle. The method includes determining values of a plurality of parameters of the operation of a first vehicle in a first road segment, determining values of the plurality of parameters for one or more second vehicles in a second road segment having similar properties to those of the first road segment, comparing the determined values of the first vehicle and the one or more second vehicles and providing an evaluation of the driving behavior of the first vehicle, responsive to the comparison.